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Low-Complexity Chase Decoding of Reed-Solomon Codes Using Channel Evaluation.
Wang, Hao; Zhang, Wei; Chang, Yanyan; Gao, Jiajing; Liu, Yanyan.
Afiliação
  • Wang H; School of Microelectronics, Tianjin University, Tianjin 300072, China.
  • Zhang W; School of Microelectronics, Tianjin University, Tianjin 300072, China.
  • Chang Y; School of Microelectronics, Tianjin University, Tianjin 300072, China.
  • Gao J; School of Microelectronics, Tianjin University, Tianjin 300072, China.
  • Liu Y; College of Electronic Information and Optical Engineering, Nankai University, Tianjin 300071, China.
Entropy (Basel) ; 24(3)2022 Mar 18.
Article em En | MEDLINE | ID: mdl-35327934
ABSTRACT
A novel time-varying channel adaptive low-complexity chase (LCC) algorithm with low redundancy is proposed, where only the necessary number of test vectors (TVs) are generated and key equations are calculated according to the channel evaluation to reduce the decoding complexity. The algorithm evaluates the error symbol numbers by counting the number of unreliable bits of the received code sequence and dynamically adjusts the decoding parameters, which can reduce a large number of redundant calculations in the decoding process. We provide a simplified multiplicity assignment (MA) scheme and its architecture. Moreover, a multi-functional block that can implement polynomial selection, Chien search and the Forney algorithm (PCF) is provided. On this basis, a high-efficiency LCC decoder with adaptive error-correcting capability is proposed. Compared with the state-of-the-art LCC (TV = 16) decoding, the number of TVs of our decoder was reduced by 50.4% without loss of the frame error rate (FER) performance. The hardware implementation results show that the proposed decoder achieved 81.6% reduced average latency and 150% increased throughput compared to the state-of-the-art LCC decoder.
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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Idioma: En Revista: Entropy (Basel) Ano de publicação: 2022 Tipo de documento: Article País de afiliação: China

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Idioma: En Revista: Entropy (Basel) Ano de publicação: 2022 Tipo de documento: Article País de afiliação: China